Kernel Methods for Dependence and Causality

Posted in Science on July 29, 2008


Kernel Methods for Dependence and Causality

Lecture slides:

  • Covariance on RKHS
  • Two Views on Kernel Methods
  • Covariance on RKHS
  • Cross-covariance operator
  • Intuition
  • Addendum on “operator”
  • Characterization of Independence
  • Measures for Dependence
  • Norms of operators
  • Empirical Estimation
  • Empirical cross-covariance operator
  • COCO Revisited
  • HSIC Revisited
  • Application of HSIC to ICA
  • ICA with HSIC
  • Experiments (speech signal)
  • Normalized Covariance
  • HSIC Revisited
  • Nonlinear dependence

Author: Kenji Fukumizu, Institute of Statistical Mathematics

Watch Video

Tags: Science, Lectures, Computer Science, Machine Learning, VideoLectures.Net, Kernel Methods